Patent Document 1 depicts an example of such kind of apparatuses used for general purposes. With this technique, the statistical change-points are detected in a following manner.
First, an occurrence probability distribution of sequentially inputted data series is learned as a first statistical model that is defined by a finite number of variables. Then, an outlier score showing a degree of difference between actual data and data predicted from the learned first statistical model for each data in the data series, and computes the moving average of the outlier scores.
Thereafter, an occurrence probability distribution of the moving average series of the outlier scores is learned as a second statistical model that is defined by a finite number of variables. Each moving average outlier score is computed based on the learned second statistical model and the moving average of the outlier scores, and it is outputted as a change-degree score of the original data. Then, the change-degree score is compared with a threshold value to detect a change-point.
Patent Document 1: Japanese Unexamined Patent Publication 2004-54370
The above-described technique is a technique that is effective in respect that it is designed to treat the outlier detection and the change-point detection uniformly in a same frame. However, this technique is not mainly directed to improve the change-point detection accuracy.
In many cases, a point where there is a relatively large change in the probability distribution of the first statistical model is a change point to be detected. However, there are cases where a point where there is no significant change in the probability distribution of the first statistical model is the change-point to be detected. In that case, a detection failure occurs. Inversely, there are cases where a point where there is relatively a large change in the probability distribution of the first statistical model is a change-point that is not to be detected. In that case, a misdetection occurs. In the field of data mining, detection of change-points has drawn an attention in association with detection of trend changes and behavior monitoring, and it is expected to improve the detection accuracy thereof still further.
An object of the present invention is to prevent a detection failure and a misdetection in a method and an apparatus for detecting a statistical change-point appeared in time-series data.